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Biomedical subjects

Peter A Vanrolleghem

Publications and source records attributed to Peter A Vanrolleghem.

At least 19 recordsLinked to original sources
PubMed2007

Multi-model statistical process monitoring and diagnosis of a sequencing batch reactor.

Biological processes exhibit different behavior depending on the influent loads, temperature, microorganism activity, and so on. It has been shown that a combination of several models can provide a suitable approach to model such processes. In the present study, we developed a multiple statistical model approach for the monitoring of biological batch processes. The proposed method consists of four main components: (1) multiway principal component analysis (MPCA) to reduce the dimensionality of data and to remove collinearity; (2) multiple models with a posterior probability for modeling different operating regions; (3) local batch monitoring by the T(2)- and Q-statistics of the specific local model; and (4) a new discrimination measure (DM) to identify when the system has shifted to a new operating condition. Under this approach, local monitoring by multiple models divides the entire historical data set into separate regions, which are then modeled separately. Then, these local regions can be supervised separately, leading to more effective batch monitoring. The proposed method is applied to a pilot-scale 80-L sequencing batch reactor (SBR) for biological wastewater treatment. This SBR is characterized by nonstationary, batchwise, and multiple operation modes. The results obtained for the pilot-scale SBR indicate that the proposed method has the ability to model multiple operating conditions, to identify various operating regions, and also to determine whether the biosystem has shifted to a new operating condition. Our findings show that the local monitoring approach can give more reliable and higher resolution monitoring results than the global model.

Biodegradation, Environmental↗
PubMed2006

Continuity-based model interfacing for plant-wide simulation: a general approach.

In plant-wide simulation studies of wastewater treatment facilities, often existing models from different origin need to be coupled. However, as these submodels are likely to contain different state variables, their coupling is not straightforward. The continuity-based interfacing method (CBIM) provides a general framework to construct model interfaces for models of wastewater systems, taking into account conservation principles. In this contribution, the CBIM approach is applied to study the effect of sludge digestion reject water treatment with a SHARON-Anammox process on a plant-wide scale. Separate models were available for the SHARON process and for the Anammox process. The Benchmark simulation model no. 2 (BSM2) is used to simulate the behaviour of the complete WWTP including sludge digestion. The CBIM approach is followed to develop three different model interfaces. At the same time, the generally applicable CBIM approach was further refined and particular issues when coupling models in which pH is considered as a state variable, are pointed out.

Algorithms↗
PubMed2006

On-line adaptive and nonlinear process monitoring of a pilot-scale sequencing batch reactor.

This article describes the application of on-line nonlinear monitoring of a sequencing batch reactor (SBR). Three-way batch data of SBR are unfolded batch-wisely, and then a adaptive and nonlinear multivariate monitoring method is used to capture the nonlinear characteristics of normal batches. The approach is successfully applied to an 80 L SBR for biological wastewater treatment, where the SBR poses an interesting challenge in view of process monitoring since it is characterized by nonstationary, batchwise, multistage, and nonlinear dynamics. In on-line batch monitoring, the developed adaptive and nonlinear process monitoring method can effectively capture the nonlinear relationship among process variables of a biological process in a SBR. The results of this pilot-scale SBR monitoring system using simple on-line measurements clearly demonstrated that the adaptive and nonlinear monitoring technique showed lower false alarm rate and physically meaningful, that is, robust monitoring results.

Bioreactors↗
PubMed2006

Carbon and hydrogen isotope fractionation by microbial methane oxidation: improved determination.

Isotope fractionation is a promising tool for quantifying methane oxidation in landfill cover soils. For good quantification an accurate determination of the isotope fractionation factor (alpha) of methane oxidation based on independent batch experiments with soil samples from the landfill cover is required. Most studies so far used data analysis methods based on approximations of the Rayleigh model to determine alpha. In this study, the two most common approximations were tested, the simplified Rayleigh approach and the Coleman method. To do this, the original model of Rayleigh was described in measurable variables, methane concentration and isotopic abundances, and fitted to batch oxidation data by means of a weighted non-linear errors-in-variables regression technique. The results of this technique were used as a benchmark to which the results of the two conventional approximations were compared. Three types of batch data were used: simulated data, data obtained from the literature, and data obtained from new batch experiments conducted in our laboratory. The Coleman approximation was shown to be acceptable but not recommended for carbon fractionation (error on alpha-1 up to 5%) and unacceptable for hydrogen fractionation (error up to 20%). The difference between the simplified Rayleigh approach and the exact Rayleigh model is much smaller for both carbon and hydrogen fractionation (error on alpha-1<0.05%). There is also a small difference when errors in both variables (methane concentration and isotope abundance) are accounted for instead of assuming an error-free independent variable. By means of theoretical calculations general criteria, not limited to methane, (13)C, or D, were developed for the validity of the simplified Rayleigh approach when using labelled compounds.

Air Pollutants↗
PubMed2006

A mathematical model linking tree sap flow dynamics to daily stem diameter fluctuations and radial stem growth.

To date, models for simulating sap flow dynamics in individual trees with a direct link to stem diameter variation include only the diameter fluctuation driven by a change in stem water storage. This paper reports results obtained with a comprehensive flow and storage model using whole-tree leaf transpiration as the only input variable. The model includes radial stem growth based on Lockhart's equation for irreversible cell expansion. It was demonstrated that including growth is essential to obtaining good simulation results. To model sap flow dynamics, capacitance of storage tissues was assumed either constant (i.e., electrical analogue approach) or variable and dependent on the water content of the respective storage tissue (i.e., hydraulic system approach). These approaches resulted in different shapes for the desorption curve used to calculate the capacitance of storage tissues. Comparison of these methods allowed detection of specific differences in model simulation of sap flow at the stem base (F(stem)) and stem diameter variation (D). Sensitivity analysis was performed to select a limited subset of identifiable parameters driving most of the variability in model predictions of F(stem) and D Both the electrical analogue and the hydraulic system approach for the flow and storage model were successfully calibrated and validated for the case of a young beech tree (Fagus sylvatica L.). Use of an objective model selection criterion revealed that the flow and storage model based on the electrical analogue approach yielded better predictions.

Calibration↗
PubMed2005

A new approach for modelling simultaneous storage and growth processes for activated sludge systems under aerobic conditions.

By critically evaluating previous models, a new mechanistic model is developed to describe simultaneous storage and growth processes occurring in activated sludge systems under aerobic conditions. Identifiability was considered an important criterion during the model development since it among others helps to increase the realiability and applicability of models to full-scale WWTPs. A second order model was proposed for description of the degradation of the storage products under famine conditions. The model is successfully calibrated by only using OUR data obtained from batch experiments. Calibrations were performed with biomass from full-scale WWTPs in Belgium and Spain. Predictions of the calibrated model were successfully confirmed using off-line PHB measurements, supporting the validity of the model. An iterative experimental design procedure was successfully applied and found to remarkably improve the parameter estimation accuracy for the growth on storage parameters K1 and K2, which used to have large confidence intervals when using standard experiments. The estimated biomass growth yield on substrate (0.58 mgCOD/mgCOD) is quite close to the theoretically expected range for heterotrophic growth. This became possible by properly accounting for the storage process. Moreover, the maximum growth rate was predicted in the range 0.7-1.3 per day. This range, albeit quite lower than the values reported for the growth-based ASM models, is believed to be more realistic. Finally, the new model is expected to better and more mechanistically describe simultaneous storage and growth activities of activated sludge systems and as such could contribute to improved design, operation and control of those systems.

Bacteria, Aerobic↗
PubMed2005

Automatic initialisation of buffer composition estimation for on-line analysis of unknown buffer solutions.

An automatic initialisation procedure for extracting useful information about buffer composition from a titration experiment is presented in this paper. The initialisation procedure identifies which buffering components are present in the sample from a relatively long list of buffers expected in the system monitored. The procedure determines approximate pKa values of the buffers and evaluates their maximum and minimum concentrations. This information is then used to start an optimisation procedure to fit the model of the buffer components to the titration data and to accurately determine buffer concentrations and pKa values. The procedure has been integrated as a software layer around the buffer capacity optimum model builder (BOMB) that fits a buffer-capacity model to a measured buffer-capacity curve to estimate model properties (pKa values and concentrations). The reliability and robustness of the resulting buffer capacity software (BCS) were tested using a titrimetric analyser simulator (TAS). The BCS was then validated off-line and on-line.

Journal Article↗
PubMed2005

Parallel hybrid modeling methods for a full-scale cokes wastewater treatment plant.

Parallel hybrid modeling methods are applied to a full-scale cokes wastewater treatment plant. Within the hybrid model structure, a mechanistic model specifies the basic dynamics of the relevant process and a non-parametric model compensates for the inaccuracy of the mechanistic model. First, a simplified mechanistic model is developed based on Activated Sludge Model No. 1 and the specific process knowledge of the cokes wastewater treatment process. Then, the mechanistic model is combined with five different non-parametric models--feedforward back-propagation neural network, radial basis function network, linear partial least squares (PLS), quadratic PLS and neural network PLS (NNPLS)--in parallel configuration. These models are identified with the same data obtained from the plant operation to predict dynamic behavior of the process. The performance of each parallel hybrid model is compared based on their ease of model building, prediction accuracy and interpretability. For this application, the parallel hybrid model with NNPLS as non-parametric model gives better performance than other parallel hybrid models. In addition, the NNPLS model is used to analyze the behavior of the operation data in the reduced space and allows for fault detection and isolation.

Bioreactors↗
PubMed2005

A rule-based screening environmental risk assessment tool derived from EUSES.

Within the context and scope of the forthcoming European Union chemical regulations (REACH), there is a need to be able to prioritise the chemicals for evaluation. Therefore, a simple, pragmatic and adequately conservative approach for the identification of substances of very low or no immediate concern at an early stage is presented. The fundamental principles and basic concepts are derived from the EU Technical Guidance Document and EUSES, and are translated into an easy-to-use rule-based system. For this development, the effect on risk characterisation ratios (RCRs) of the key environmental parameters in EUSES was quantified (taking into account several standardised chemical release scenarios). Using statistical analysis, ranges were identified for each key parameter, within which the end result of the assessment was not significantly affected. This information was then translated into a lookup table from which environmental risk characterisation ratios can be directly read as a function of a few parameters.

Environmental Monitoring↗
PubMed2005

Detailed spatio-temporal solids concentration profiling during batch settling of activated sludge using a radiotracer.

In building and tuning good settling models for secondary clarifiers of wastewater treatment plants, there is a need for measured continuous solids concentration profiles during batch settling. Conventional measuring techniques have difficulties in recording this kind of data, either because they are invasive, or because of the low solids concentration and/or solids density of activated sludge. This paper investigates a novel non-invasive measurement technique borrowed from nuclear medicine, using a solids radiotracer and gamma cameras, to obtain solids concentration profiles during the batch settling of activated sludge, in a pilot-scale column with a height of 1m. The technique does not disturb the settling process, does not alter the settling characteristics, gives profiles every minute and every few millimeters, and is capable of measuring in a range of 0-25 g/l with high accuracy. Dynamic solids concentration profile measurements were performed for sludges of different wastewater treatment plants, and at different initial concentrations. The results show a quantitative representation of the settling process, and reveal hindered and compression settling.

Gamma Cameras↗
PubMed2005

A critical comparison of systematic calibration protocols for activated sludge models: a SWOT analysis.

Modelling activated sludge systems has gained an increasing momentum after the introduction of activated sludge models (ASMs) in 1987. Application of dynamic models for full-scale systems requires essentially a calibration of the chosen ASM to the case under study. Numerous full-scale model applications have been performed so far which were mostly based on ad hoc approaches and expert knowledge. Further, each modelling study has followed a different calibration approach: e.g. different influent wastewater characterization methods, different kinetic parameter estimation methods, different selection of parameters to be calibrated, different priorities within the calibration steps, etc. In short, there was no standard approach in performing the calibration study, which makes it difficult, if not impossible, to (1) compare different calibrations of ASMs with each other and (2) perform internal quality checks for each calibration study. To address these concerns, systematic calibration protocols have recently been proposed to bring guidance to the modeling of activated sludge systems and in particular to the calibration of full-scale models. In this contribution four existing calibration approaches (BIOMATH, HSG, STOWA and WERF) will be critically discussed using a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis. It will also be assessed in what way these approaches can be further developed in view of further improving the quality of ASM calibration. In this respect, the potential of automating some steps of the calibration procedure by use of mathematical algorithms is highlighted.

Algorithms↗
PubMed2005

Model study of short-term dynamics of secondary treatment reed beds at Saxby (Leicestershire, UK).

Relatively simple black-box models, such as the well-known k-C* model, are commonly applied to design horizontal sub-surface flow constructed treatment wetlands. Important shortcomings of this model are the oversimplification of reality on the one hand, and the inability to predict short-term effluent dynamics on the other. A possible solution for these drawbacks could be the application of dynamic compartmental models. This article reports on the calibration requirements and the simulation results of such a dynamic model. A quantitative sensitivity analysis was used to identify the most sensitive parameters after which model predictions were optimized by adjusting those parameter values. Model fits were acceptable but missed some of the short-term dynamics observed in reality. At this point, it might therefore still be unwise to use the model as a design tool. Further model adjustments and calibration efforts are needed to enhance its reliability.

Biodegradation, Environmental↗
PubMed2004

Adaptive multiscale principal component analysis for on-line monitoring of a sequencing batch reactor.

In recent years, multiscale monitoring approaches, which combine principal component analysis (PCA) and multi-resolution analysis (MRA), have received considerable attention. These approaches are potentially very efficient for detecting and analyzing diverse ranges of faults and disturbances in chemical and biochemical processes. In this work, multiscale PCA is proposed for fault detection and diagnosis of batch processes. Using MRA, measurement data are decomposed into approximation and details at different scales. Adaptive multiway PCA (MPCA) models are developed to update the covariance structure at each scale to deal with changing process conditions. Process monitoring by a unifying adaptive multiscale MPCA involves combining only those scales where significant disturbances are detected. This multiscale approach facilitates diagnosis of the detected fault as it hints to the time-scale under which the fault affects the process. The proposed adaptive multiscale method is successfully applied to a pilot-scale sequencing batch reactor for biological wastewater treatment.

Algorithms↗
PubMed2004

Modeling and simulation of oxygen-limited partial nitritation in a membrane-assisted bioreactor (MBR).

Combination of a partial nitritation process and an anaerobic ammonium oxidation process for the treatment of sludge reject water has some general cost-efficient advantages compared to nitrification-denitrification. The integrated process features two-stage autotrophic conversion of ammonium via nitrite to dinitrogen gas with lower demand for oxygen and no external carbon requirement. A nitrifying membrane-assisted bioreactor (MBR) for the treatment of sludge reject water was operated under continuous aeration at low dissolved oxygen (DO) concentrations with the purpose of generating nitrite accumulation. Microfiltration was applied to allow a high sludge retention time (SRT), resulting in a stable partial nitritation process. During start-up of the MBR, oxygen-limited conditions were induced by increasing the ammonium loading rate and decreasing the oxygen transfer. At a loading rate of 0.9 kg N m(-3) d(-1) and an oxygen concentration below 0.1 mg DO L(-1), conversion to nitrite was close to 50% of the incoming ammonium, thereby yielding an optimal effluent within the stoichiometric requirements for subsequent anaerobic ammonium oxidation. A mathematical model for ammonium oxidation to nitrite and nitrite oxidation to nitrate was developed to describe the oxygen-limited partial nitritation process within the MBR. The model was calibrated with in situ determinations of kinetic parameters for microbial growth, reflecting the intrinsic characteristics of the ammonium oxidizing growth system at limited oxygen availability and high sludge age. The oxygen transfer coefficient (K(L)a) and the ammonium-loading rate were shown to be the appropriate operational variables to describe the experimental data accurately. The validated model was used for further steady state simulation under different operational conditions of hydraulic retention time (HRT), K(L)a, temperature and SRT, with the intention to support optimized process design. Simulation results indicated that stable nitrite production from sludge reject water was feasible with this process even at a relatively low temperature of 20 degrees C with HRT down to 0.25 days.

Bacteria, Anaerobic↗
PubMed2004

Transient response of aerobic and anoxic activated sludge activities to sudden substrate concentration changes.

The state-of-the-art understanding of activated sludge processes as summarized in activated sludge models (ASMs) predicts an instantaneous increase in the biomass activity (which is measured, e.g., by the corresponding respiration rate OUR, NUR, etc.) under sudden substrate concentration changes. Experimental data (e.g., short-term batch respiration experiments under aerobic or anoxic conditions) collected for the calibration of the dynamic models (ASMs) often exhibit a transient phenomenon while attaining maximum activity, which cannot be explained by the current understanding of the activated sludge process. That transient phenomenon exhibits itself immediately upon addition of a substrate source to an endogenously respiring activated sludge sample and it usually takes a few minutes until the activated sludge reaches its maximum possible rate under given environmental conditions. This discrepancy between the state-of-the-art model and the experimental data is addressed in detail in this investigation. It is shown that the discrepancy is not caused by an error in the experimental set-up/data but it is rather due to model inadequacy. Among the hypotheses proposed, it appears that this transient response of the activated sludge most likely results from the sequence of intracellular reactions involved in substrate degradation by the activated sludge. Results from studies performed elsewhere with pure cultures (S. cerevisae and E. coli) support the hypothesis. The transient phenomenon can be described by a dynamic metabolic network model or by a simple first-order model, as adopted in this study. The transient phenomenon occurring in short-term batch respiration experiments is shown to interfere severely with parameter estimation if not modeled properly (2.8%, 11.5%, and 16.8% relative errors [average of three experiments] on Y(H), micro(maxH), and K(S), respectively). Proper modeling of this transient phenomenon whose time constant is on the order of minutes (1 to 3 min) is expected to contribute fundamentally to a better understanding and modeling of Orbal, carousel, and SBR-type treatment plants with fast-alternating process conditions, although such studies are beyond the scope of this report.

Aerobiosis↗
PubMed2004

Model-based design of horizontal subsurface flow constructed treatment wetlands: a review.

The increasing application of constructed wetlands for wastewater treatment coupled with increasingly strict water quality standards is an ever growing incentive for the development of better process design tools. This paper reviews design models for horizontal subsurface flow constructed treatment wetlands, ranging from simple rules of thumb and regression equations, to the well-known first-order k-C* models, Monod-type equations and more complex dynamic, compartmental models. Especially highlighted in this review are the model constraints and parameter uncertainty. A case study has been used to demonstrate the model output variability and to unravel whether or not more complex but also less manageable models offer a significant advantage to the designer.

Ecosystem↗